DBMS > H2 vs. IRONdb vs. SQLite vs. Teradata Aster vs. Transbase

System Properties Comparison H2 vs. IRONdb vs. SQLite vs. Teradata Aster vs. Transbase

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Widely used embeddable, in-process RDBMS

Platform for big data analytics on multistructured data sources and types

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.h2database.com

www.circonus.com/solutions/time-series-database/

www.sqlite.org

www.transaction.de/en/products/transbase.html

Technical documentation

www.h2database.com/html/main.html

docs.circonus.com/irondb/category/getting-started

www.sqlite.org/docs.html

www.transaction.de/en/products/transbase/features.html

Developer

Thomas Mueller

Circonus LLC.

Dwayne Richard Hipp

Teradata

Transaction Software GmbH

Initial release

2005

2017

2000

2005

1987

Current release

2.2.220, July 2023

V0.10.20, January 2018

3.45.3 (15 April 2024), April 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Public Domain

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

Linux

server-less

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

dynamic column types

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

not rigid because of 'dynamic typing' concept.

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
ODBC

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
Python
R

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes, in Lua

R packages

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

configurable replication factor, datacenter aware

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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